91 lines
2.7 KiB
Python
91 lines
2.7 KiB
Python
# Copyright 2022 EleutherAI and The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import TYPE_CHECKING
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from transformers.utils import (
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OptionalDependencyNotAvailable,
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_LazyModule,
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is_sentencepiece_available,
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is_tokenizers_available,
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is_torch_available,
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)
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_import_structure = {
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"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
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}
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try:
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if not is_sentencepiece_available():
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["tokenization_llama"] = ["LlamaTokenizer"]
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try:
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if not is_tokenizers_available():
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["tokenization_llama_fast"] = ["LlamaTokenizerFast"]
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try:
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if not is_torch_available():
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_llama"] = [
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"LlamaForCausalLM",
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"LlamaModel",
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"LlamaPreTrainedModel",
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"LlamaForSequenceClassification",
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]
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if TYPE_CHECKING:
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from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig
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try:
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if not is_sentencepiece_available():
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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pass
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else:
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from .tokenization_llama import LlamaTokenizer
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try:
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if not is_tokenizers_available():
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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pass
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else:
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from .tokenization_llama_fast import LlamaTokenizerFast
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try:
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if not is_torch_available():
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raise OptionalDependencyNotAvailable()
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except OptionalDependencyNotAvailable:
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pass
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else:
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from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel
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else:
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import sys
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sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
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